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astro300_f16:day8 [2016/10/03 04:55]
bethmcbride [Homework]
astro300_f16:day8 [2016/10/03 05:26] (current)
ccheng [Homework]
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   - Section video-taping is happening this week. We will send you a link to your section video by the end of the week. Watch it, and complete the {{:​video.pdf|Section Video Recap Worksheet}} (due 10/12, next week!).   - Section video-taping is happening this week. We will send you a link to your section video by the end of the week. Watch it, and complete the {{:​video.pdf|Section Video Recap Worksheet}} (due 10/12, next week!).
   - Bring your lesson plan notebooks to 375 next week.    - Bring your lesson plan notebooks to 375 next week. 
-  - Read papers: +  - Look through the abstracts from some of the following conference proceedings. Choose one paper to read (it should be at least four pages long) and answer the questions at the bottom of this page. 
-  * Learning @ Scale: mainly focused on MOOC learning, but does have research on using student datahttp://​dl.acm.org/​citation.cfm?​id=2876034 +  * Learning @ Scale: mainly focused on learning ​from MOOCs (massively open online courses), but also includes ​research on using student data to understand aspects of learning: ​http://​dl.acm.org/​citation.cfm?​id=2876034 
-  * ICLS: International Conference of the Learning Sciences, ​best research in the field, includes some research in higher educationhttps://​www.isls.org/​icls/​2016/​index.html (see proceedings,​ volumes 1 & 2 on homepage) +  * ICLS: International Conference of the Learning Sciences, ​top research ​conference ​in the field and mainly focuses on STEM education, includes some research in higher educationhttps://​www.isls.org/​icls/​2016/​index.html (see proceedings,​ volumes 1 & 2 on homepage) 
-  * NARST: National Association of Research in Science Teaching, mainly focused on practitioners and applied ​researchhttp://​narst.org/​annualconference/​2016_Narst_International_Conference_Program.pdf +  * NARST: National Association of Research in Science Teaching, mainly focused on practitioners and research ​that comes from classrooms or is being applied to classrooms: ​http://​narst.org/​annualconference/​2016_Narst_International_Conference_Program.pdf 
-  * EDM: Educational Data Mining, mainly focused on machine learning as a method ​of understanding ​student learninghttp://​www.educationaldatamining.org/​EDM2016/​proceedings/​edm2016_proceedings.pdf +  * EDM: Educational Data Mining, mainly focused on machine learning as a method ​for using data to understand ​student learninghttp://​www.educationaldatamining.org/​EDM2016/​proceedings/​edm2016_proceedings.pdf 
-  * AIED: Artificial Intelligence in Education, more comprehensive ​data mining and methods ​(including natural language processing) as a means to understand student learninghttp://​www.springer.com/​us/​book/​9783319197722 +  * AIED: Artificial Intelligence in Education, more comprehensive ​methodology than EDM (including natural language processing) as a means to understand student learninghttp://​www.springer.com/​us/​book/​9783319197722 
-  * AERA: American Educational Research Association,​ biggest conference for presenting new work, but the proceedings are a real pain to sift throughhttp://​www.aera.net/​Publications/​Online-Paper-Repository/​AERA-Online-Paper-Repository+  * AERA: American Educational Research Association, ​the biggest conference for presenting new work in all areas of education (including higher education, STEM education, etc.), but the proceedings are a pain to sift throughhttp://​www.aera.net/​Publications/​Online-Paper-Repository/​AERA-Online-Paper-Repository 
 + 
 +Answer these questions about your articles: 
 +  * What is the title? 
 +  * What were the main take-aways (conclusions) from the article? 
 +  * What methods did the authors use to come to their conclusions?​ 
 +  * Do you agree with the conclusions?​ What critiques do you have about the paper? 
 +  * What did you find most interesting about your article or about the proceedings in general?